TaxoNN: A Light-Weight Accelerator for Deep Neural Network Training. - Reza Hojabr; Kamyar Givaki; Kossar Pourahmadi; Parsa Nooralinejad; Ahmad Khonsari; Dara Rahmati; M. Hassan Najafi (ISCAS, 2020)

A Simple Baseline for Low-Budget Active Learning. - Kossar Pourahmadi; Parsa Nooralinejad; Hamed Pirsiavash (CoRR, 2021)

Constrained Mean Shift Using Distant yet Related Neighbors for Representation Learning. - K. L. Navaneet; Soroush Abbasi Koohpayegani; Ajinkya Tejankar; Kossar Pourahmadi; Akshayvarun Subramanya; Hamed Pirsiavash (ECCV (31), 2022)

PRANC: Pseudo RAndom Networks for Compacting deep models. - Parsa Nooralinejad; Ali Abbasi 008; Soroush Abbasi Koohpayegani; Kossar Pourahmadi Meibodi; Rana Muhammad Shahroz Khan; Soheil Kolouri; Hamed Pirsiavash (ICCV, 2023)

Compact3D: Compressing Gaussian Splat Radiance Field Models with Vector Quantization. - K. L. Navaneet; Kossar Pourahmadi Meibodi; Soroush Abbasi Koohpayegani; Hamed Pirsiavash (CoRR, 2023)

CompGS: Smaller and Faster Gaussian Splatting with Vector Quantization. - K. L. Navaneet; Kossar Pourahmadi Meibodi; Soroush Abbasi Koohpayegani; Hamed Pirsiavash (ECCV (32), 2024)

MoIN: Mixture of Introvert Experts to Upcycle an LLM. - Ajinkya Tejankar; Navaneet K. L.; Ujjawal Panchal; Kossar Pourahmadi; Hamed Pirsiavash (CoRR, 2024)